Modeling latent information in voting data with Dirichlet process priors

Modeling latent information in voting data with Dirichlet process priors

We apply a specialized Bayesian method that helps us deal with the methodological challenge of unobserved heterogeneity among immigrant voters. Our approach is based on generalized linear mixed Dirichlet models (GLMDMs) where random effects are specified semiparametrically using a Dirichlet process...

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Bibliographic Details
Main Authors:	Traunmüller, R, Murr, A, Gill, J
Format:	Journal article
Language:	English
Published:	Oxford University Press 2014

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